Hello SymPy developers,

I am excited to share my interest in contributing to SymPy by enhancing its 
capabilities in multivariate polynomial arithmetic and factorization. 
Currently, SymPy utilizes Kronecker's method for multivariate polynomial 
factorization, which, while a solid foundation, lacks the efficiency needed 
for practical applications. I propose implementing more advanced 
algorithms, such as Wang's EEZ-GCD or Gao's approach using partial 
differential equations, to boost the efficiency and usability of 
multivariate polynomial operations in SymPy.

My main question is: Does expanding SymPy's support for efficient 
multivariate polynomial arithmetic and factorization fit within the 
project's current development roadmap and priorities?

If this aligns with SymPy's objectives, I am eager to contribute to this 
initiative. I have a strong background in algebra and computational 
mathematics, which I believe will be valuable in addressing this challenge. 
I am ready to delve into the implementation details, research 
state-of-the-art algorithms, and develop a concrete plan to integrate these 
enhancements into SymPy.

To help facilitate this process, I would greatly appreciate any guidance on:

Recommended resources or existing work within SymPy that I should review.

Potential challenges or considerations that may arise when implementing 
efficient multivariate polynomial arithmetic and factorization algorithms.

I am particularly interested in exploring methods like Yan's geobuckets, 
heap-based algorithms (Monagan & Pearce), and advanced GCD algorithms such 
as Zippel's SPMOD or Musser's EZ-GCD. Additionally, I am open to extending 
these methods to polynomials with coefficients in algebraic domains or 
implementing efficient factorization over finite fields.

Thank you for your time and consideration. I look forward to your response 
and am excited about the opportunity to contribute to SymPy's development.


Best regards,  

Pratyksh Gupta

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